Cox Predicted Survival

This is a slightly modified version of Therneau's survfit.coxph function. The difference is that survfit.cph assumes that x=TRUE,y=TRUE were specified to the fit. This assures that the environment in effect at the time of the fit (e.g., automatic knot estimation for spline functions) is the same one used for basing predictions.

Usage

# S3 method for class 'cph'
survfit(formula, newdata, se.fit=TRUE, conf.int=0.95, 
        individual=FALSE, type=NULL, vartype=NULL,
        conf.type=c('log', "log-log", "plain", "none"), censor=TRUE, id, ...)

Arguments

formula

a fit object from cph or coxph see survfit.coxph

newdata,se.fit,conf.int,individual,type,vartype,conf.type,censor,id

see survfit. If individual is TRUE, there must be exactly one Surv object in newdata. This object is used to specify time intervals for time-dependent covariate paths. To get predictions for multiple subjects with time-dependent covariates, specify a vector id which specifies unique hypothetical subjects. The length of id should equal the number of rows in newdata.

...

Not used

Value

see survfit.coxph

See also

survest.cph